10; const a = document.createElement('a'); a.href = blobUrl; a.download = 'AI_Dectectors.csv'; a.style.display = 'none'; document.body.appendChild(a); a.dispatchEvent(new MouseEvent('click')); document.body.removeChild(a); setTimeout(() => { window.URL.revokeObjectURL(blobUrl); }, 100); return false; } catch (error) { console.error('Download failed:', error); alert('Download failed. Please try again.'); } } downloadFile(event); "> AI Dectector data

What story can you tell, and deduction can you make from Figure 9 below? How would you replicate it? What would you add?

Figure 9: AI Detectors

13 AI Generated Summary and Podcast

This excerpt from “Groups – Applied Metaphors: Learning TRIZ, Complexity, Data/Stats/ML using Metaphors” provides a comprehensive guide to understanding and utilizing box plots for data visualization and analysis. The text explores the purpose, functionality, and application of box plots within the context of exploring relationships between quantitative and qualitative variables. The author illustrates these concepts using a case study of the “gss_wages” dataset, examining wage discrepancies by gender, occupation, age, and education. Through this analysis, the author highlights the effectiveness of box plots in visualizing distributions, identifying outliers, and comparing groups, providing valuable insights into the complexities of data. The text concludes with a call to action, encouraging readers to explore real-world datasets and apply these techniques to uncover hidden trends and patterns within data.

14 References

  1. Bevans, R. (2023, June 22). An Introduction to t Tests | Definitions, Formula and Examples. Scribbr. https://www.scribbr.com/statistics/t-test/

  2. Brown, Angus. (2008). The Strange Origins of the t-test. Physiology News | No. 71 | Summer 2008| https://static.physoc.org/app/uploads/2019/03/22194755/71-a.pdf

  3. Stephen T. Ziliak.(2008). Guinnessometrics: The Economic Foundation of “Student’s” t. Journal of Economic Perspectives—Volume 22, Number 4—Fall 2008—Pages 199–216. https://pubs.aeaweb.org/doi/pdfplus/10.1257/jep.22.4.199

  4. https://quillette.com/2024/08/03/xy-athletes-in-womens-olympic-boxing-paris-2024-controversy-explained-khelif-yu-ting/

  5. Senefeld JW, Lambelet Coleman D, Johnson PW, Carter RE, Clayburn AJ, Joyner MJ. Divergence in Timing and Magnitude of Testosterone Levels Between Male and Female Youths. JAMA. 2020;324(1):99–101. doi:10.1001/jama.2020.5655. https://jamanetwork.com/journals/jama/fullarticle/2767852

  6. Doriane Lambelet Coleman.(2017) Sex in Sport, 80 Law and Contemporary Problems. Available at: https://scholarship.law.duke.edu/lcp/vol80/iss4/5

R Package Citations
Package Version Citation
ggridges 0.5.6 Wilke (2024)
NHANES 2.1.0 Pruim (2015)
TeachHist 0.2.1 Lange (2023)
TeachingDemos 2.13 Snow (2024)
visualize 4.5.0 Balamuta (2023)
Balamuta, James. 2023. visualize: Graph Probability Distributions with User Supplied Parameters and Statistics. https://CRAN.R-project.org/package=visualize.
Lange, Carsten. 2023. TeachHist: A Collection of Amended Histograms Designed for Teaching Statistics. https://CRAN.R-project.org/package=TeachHist.
Pruim, Randall. 2015. NHANES: Data from the US National Health and Nutrition Examination Study. https://CRAN.R-project.org/package=NHANES.
Snow, Greg. 2024. TeachingDemos: Demonstrations for Teaching and Learning. https://CRAN.R-project.org/package=TeachingDemos.
Wilke, Claus O. 2024. ggridges: Ridgeline Plots in ggplot2. https://CRAN.R-project.org/package=ggridges.